Combined Utility of Functional MRI, Cortical Mapping, and Frameless Stereotaxy in the Resection of Lesions in Eloquent Areas of Brain in Children
Bibliographic record
Abstract
We studied 16 children with lesions in the eloquent brain to determine if the amalgamation of information from functional magnetic resonance imaging (fMRI), frameless stereotaxy, and direct cortical mapping and recording could facilitate the excision of these lesions while minimizing potential neurological deficits. The mean age of the children was 10 years. Fourteen children presented with seizures. All lesions were located in or near eloquent cerebral cortex. fMRI was successful in all patients in delineating the relationship between the lesion and regions of task-activated cortex. The ISG wand was utilized in all cases for scalp and bone flap placement, and for intraoperative localization of the lesion. Direct cortical stimulation or recording of phase reversals with somatosensory evoked potentials helped delineate the central sulcus and language cortex in patients with lesions near the motor or language cortex. Intraoperative electrocorticography (ECoG) was utilized in all patients who presented with seizures to guide the extent of resection of the epileptiform cortex. Ten children had benign cerebral neoplasms, nine of which were totally resected. The other diagnoses included vascular malformations, Sturge-Weber, tuberous sclerosis, Rasmussen's encephalitis, and primitive neuroectodermal tumor. Only 1 patient with a left Rolandic AVM developed a new neurological deficit postoperatively. Thirteen of fourteen patients who presented with seizure disorders were rendered either seizure free or improved in terms of seizure control postoperatively. Follow-up has ranged from 12 to 18 months, with a mean follow-up of 15 months. We conclude that the techniques of fMRI, frameless stereotaxy, direct cortical stimulation and recording can be utilized in sequence to accurately localize intracerebral lesions in eloquent brain, and to reduce the morbidity of resecting these lesions in children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".